Jingyan Wang is a Research Assistant Professor at the Toyota Technological Institute at Chicago. She was previously a postdoctoral fellow at Georgia Tech, affiliated with the School of Industrial and Systems Engineering and the Algorithm and Randomness Center. She received her PhD in Computer Science from Carnegie Mellon University and her B.S. in Electrical Engineering and Computer Sciences from UC Berkeley. She uses tools from statistics and machine learning to understand and improve evaluation systems, such as those involving hiring, admissions, grading, and peer review. Her interdisciplinary research has been published in machine learning, artificial intelligence, human computation, and economics and computation. She was the recipient of the Best Student Paper Award at AAMAS 2019 and was selected as a Rising Star in EECS and in Data Science.
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